Training & Development

Being coachable isn’t just a skill. It’s the switch that activates your career momentum. But most leaders don’t lose their edge from a lack of confidence. They lose it by becoming uncoachable. What does that look like in the real world? A CEO I coached once told me: “Let’s keep the feedback light. This offsite’s more for my team.” Then on day two, a brave direct report said: “We don’t speak up because it doesn’t feel safe to disagree with you.” The room went still. The CEO paused and said: “That’s not how I want to lead.” That moment changed everything. Six months later: ✅ Retention improved for the first time in 5 years ✅ They hit their goals 3 months early ✅ Engagement and performance spiked Why? Not because he knew more. But because he became coachable. Start with these micro-steps: 1. Ask before assuming. → “Can you help me understand what you saw?” Curiosity creates clarity. 2. Track your defensiveness. → “What truth might I be resisting right now?” Awareness is the first unlock. 3. Say: ‘I didn’t see that.’ → “Thanks for the feedback. I hadn’t noticed it.” That’s leadership, not weakness. 4. Invite micro-feedback. → “What’s one thing I could try differently next time?” Tiny shifts create trust. 5. Reflect before reacting. → “What part of this feels uncomfortable, but true?” Growth lives in that tension. 📊 Research shows coachable leaders build teams with: → 31% faster team development → 39% higher engagement and performance (Source: Zenger Folkman) Because people don’t follow perfect leaders. They follow learning ones. ❓What was your most coachable moment? ♻️ Tag a leader who listens, adapts, and rises. ➕ Follow Loren Rosario - Maldonado, PCC for human-centered leadership insights.

Master the core SQL commands that drive 80% of tasks. This post focuses on practical, real-world applications of SQL for maximum impact. Fundamental SQL Commands 1. 𝗦𝗘𝗟𝗘𝗖𝗧: Retrieving specific data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚏𝚒𝚛𝚜𝚝_𝚗𝚊𝚖𝚎, 𝚕𝚊𝚜𝚝_𝚗𝚊𝚖𝚎, 𝚎𝚖𝚊𝚒𝚕 𝙵𝚁𝙾𝙼 𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛𝚜;    2. 𝗪𝗛𝗘𝗥𝗘: Filtering results        𝚆𝙷𝙴𝚁𝙴 𝚙𝚞𝚛𝚌𝚑𝚊𝚜𝚎_𝚍𝚊𝚝𝚎 >= '𝟸𝟶𝟸𝟹-𝟶𝟷-𝟶𝟷' 𝙰𝙽𝙳 𝚝𝚘𝚝𝚊𝚕_𝚜𝚙𝚎𝚗𝚝 > 𝟷𝟶𝟶𝟶;    3. 𝗚𝗥𝗢𝗨𝗣 𝗕𝗬: Aggregating data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚌𝚊𝚝𝚎𝚐𝚘𝚛𝚢, 𝚂𝚄𝙼(𝚜𝚊𝚕𝚎𝚜_𝚊𝚖𝚘𝚞𝚗𝚝) 𝙰𝚂 𝚝𝚘𝚝𝚊𝚕_𝚜𝚊𝚕𝚎𝚜    𝙵𝚁𝙾𝙼 𝚜𝚊𝚕𝚎𝚜    𝙶𝚁𝙾𝚄𝙿 𝙱𝚈 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚌𝚊𝚝𝚎𝚐𝚘𝚛𝚢;    4. 𝗢𝗥𝗗𝗘𝗥 𝗕𝗬: Sorting data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚗𝚊𝚖𝚎, 𝚜𝚝𝚘𝚌𝚔_𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚢    𝙵𝚁𝙾𝙼 𝚒𝚗𝚟𝚎𝚗𝚝𝚘𝚛𝚢    𝙾𝚁𝙳𝙴𝚁 𝙱𝚈 𝚜𝚝𝚘𝚌𝚔_𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚢 𝙰𝚂𝙲;    5. 𝗝𝗢𝗜𝗡: Combining related data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚘.𝚘𝚛𝚍𝚎𝚛_𝚒𝚍, 𝚌.𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛_𝚗𝚊𝚖𝚎, 𝚘.𝚘𝚛𝚍𝚎𝚛_𝚍𝚊𝚝𝚎    𝙵𝚁𝙾𝙼 𝚘𝚛𝚍𝚎𝚛𝚜 𝚘    𝙸𝙽𝙽𝙴𝚁 𝙹𝙾𝙸𝙽 𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛𝚜 𝚌 𝙾𝙽 𝚘.𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛_𝚒𝚍 = 𝚌.𝚒𝚍;    Advanced SQL Techniques 1. 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀: Nested queries for complex conditions        SELECT product_name, price    FROM products    WHERE price > (SELECT AVG(price) FROM products);    2. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗧𝗮𝗯𝗹𝗲 𝗘𝘅𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻𝘀 (𝗖𝗧𝗘): Simplifying complex queries        WITH monthly_sales AS (    SELECT EXTRACT(MONTH FROM sale_date) AS month, SUM(amount) AS total    FROM sales    GROUP BY EXTRACT(MONTH FROM sale_date)    )    SELECT month, total    FROM monthly_sales    WHERE total > 100000;    3. 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: Calculations across row sets        SELECT    department,    employee_name,    salary,    RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS salary_rank    FROM employees;    4. 𝗖𝗔𝗦𝗘 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁𝘀: Conditional categorization        SELECT    customer_id,    CASE    WHEN lifetime_value > 10000 THEN 'VIP'    WHEN lifetime_value > 5000 THEN 'Premium'    ELSE 'Standard'    END AS customer_segment    FROM customer_data;    Optimization Tips - Use indexes on frequently filtered columns - Avoid SELECT * and only retrieve necessary columns - Use EXPLAIN ANALYZE to understand query execution plans Learning Strategy 1. Start with simple SELECT queries on a sample database 2. Progress to filtering and sorting data 3. Practice joins with multiple tables 4. Explore advanced techniques with real datasets 5. Participate in online SQL challenges and forums By mastering these SQL commands and techniques, you'll be well-equipped to handle a wide range of data analysis tasks efficiently. Regular practice with diverse datasets will solidify your skills. What's your favorite SQL trick for streamlining data ? Share your insights below!

As GenAI becomes more ubiquitous, research alarmingly shows that women are using these tools at lower rates than men across nearly all regions, sectors, and occupations.   A recent paper from researchers at Harvard Business School, Berkeley, and Stanford synthesizes data from 18 studies covering more than 140k individuals worldwide.   Their findings:   • Women are approximately 22% less likely than men to use GenAI tools • Even when controlling for occupation, age, field of study, and location, the gender gap remains • Web traffic analysis shows women represent only 42% of ChatGPT users and 31% of Claude users   Factors Contributing the to Gap:   - Lack of AI Literacy: Multiple studies showed women reporting significantly lower familiarity with and knowledge about generative AI tools as the largest gender gap driver. - Lack of Training & Confidence: Women have lower confidence in their ability to effectively use AI tools and more likely to report needing training before they can benefit from generative AI.   - Ethical Concerns & Fears of Judgement: Women are more likely to perceive AI usage as unethical or equivalent to cheating, particularly in educational or assignment contexts. They’re also more concerned about being judged unfairly for using these tools.   The Potential Impacts: - Widening Pay & Opportunity Gap: Considerably lower AI adoption by women creates further risk of them falling behind their male counterparts, ultimately widening the gender gap in pay and job opportunities. - Self-Reinforcing Bias: AI systems trained primarily on male-generated data may evolve to serve women's needs poorly, creating a feedback loop that widens existing gender disparities in technology development and adoption.   As educators and AI literacy advocates, we face an urgent responsibility to close this gap and simply improving access is not enough. We need targeted AI literacy training programs, organizations committed to developing more ethical GenAI, and safe and supportive communities like our Women in AI + Education to help bridge this expanding digital divide.   Link to the full study in the comments. And a link also to learn more or join our Women in AI + Education Community. AI for Education #Equity #GenAI #Ailiteracy #womeninAI

Let me fix your 1:1 meetings in 90 seconds. It only requires two changes: - Make it their meeting, not yours - Ask questions, don't give directions Here's how to do it: 1. Make It Their Meeting Relinquishing ownership of this meeting is the same as delegating any other work. - Define what excellent looks like - Hold them accountable - Coach to success - Don't step in But how do I get what I need to lead? That's part 2... 2. Good Questions >> Great Directions The easiest way to align on expectations is to preview the questions you want them to answer. If they can answer these well, you can have confidence that they are excellently managing their area (even individual contributors). Here are mine: ✅ How are you doing? Want people to produce outsized results? You need to care personally. You'll only know when to show up for them if you know them well. Get a tepid response? Ask again. ✅ What's most important for us to focus on? If it is their meeting, they set the agenda. Not only are you empowering them, but you also get to learn how they think. This will help you anticipate what they might miss. ✅ How are you tracking against your goals? I want data. Clear metrics. The more tangible, the better. If the goal isn't easily measured, then I want a few qualitative angles that are in tension to surface the truth. Don't be afraid to ask, "What is your confidence?" ✅ Are there notable Wins/Losses to discuss? The specific Win or Loss doesn't matter to me as much as: a) Can they separate big from small? b) Are they proactively sharing? My probing questions should uncover very little. ✅ What problems are you focused on solving? I don't expect perfection if we're driving hard and creating value. Instead, I want them to have command of their area. - Do they know the problems? - Do the solutions make sense? - Are they making good progress? ✅ How are your people doing? Your people are only as good as those that support them. Even individual contributors rely on others. Help them practice sizing up those around them. Make empathy a habit. ✅ How are you getting better? When your team is filled with curious and compounding professionals, the result is a team that's agile and resilient. To get there, you must coach those who coach others. ✅ How can I support your success? Hopefully, you've done this throughout the conversation, but it never hurts to ask them directly, "What else do you need to win?" - Remove obstacles. - Provide resources. - Repeat often. If you want access to the management dashboard template I used to delegate my 1:1 meetings, subscribe to my MGMT Playbook for free access. https://lnkd.in/eAA-CJrJ You get dozens of playbooks and templates for critical management moments. It's the advice your boss should be giving you but probably isn't. P.S. Repost to share this with your network ♻️. And follow Dave Kline for more great posts.

Machine learning education is broken, especially for those who aspire to start solving real-world problems at a company. Most classes, courses, and books start with a dataset and show you how to train a model. dataset → model This is, at best, 5% of the work you'll need to do. Real-life problems never start with a "dataset," and they never end after you finish training a model. I've never seen a company with a "dataset" ready to go. In fact, most companies don't even have any data at all. It's your job to determine what data you need and how to collect it. Here is a simplified process that will give you a better idea of how people solve real problems: problem → framing → data → model → feedback → repeat Before understanding the problem and deciding how you'll frame it to solve it, you can't start thinking about datasets. A few other challenges: 1. How do you get data from its source? 2. Is the data diverse enough to solve the problem? 3. Do you have enough data? 4. How is the data biased? 5. How frequently does the data change? 6. How sensitive is the data? 7. Are there missing, inconsistent, or incorrect values? 8. How noisy is the data? 9. How can you trace back every piece of data to its source? 10. Are there any legal restrictions on the use of the data? 11. How do you scale as data grows? 12. How quickly does the data become stale? Building systems that work requires a lot of effort. I wish more people would talk about this.

Cold Calling Is Dying. Here’s What’s Replacing It. The numbers don’t lie: • Cold call success rates have dropped to 2.3% in 2025, down from 4.8% last year (Cognism). • 72% of sales calls never reach a person, and it takes 8+ dials to connect with just one prospect. • Only 28% of reps still view cold calling as effective. Meanwhile, high-performing teams are doing something different. Research-Driven, Insight-Led Outreach Wins: • Reps who thoroughly research their prospects are 3x more likely to succeed (Clevenio). • Prospect-specific research can lift conversions by ~30%. • Insight-led outreach builds trust before a call is ever placed. Email and Social Are Outpacing Phone-First Approaches: • Personalized cold emails outperform generic ones by 32%; average reply rates are 8–9%. • 78% of social sellers outsell peers, and social-enabled teams hit quota 66% more often. Takeaway: 1. The call is no longer the first touchpoint. It’s the third or maybe the fourth; it’s only viable once you have demonstrable engagement via other channels. 2. Buyers start with research—so should you. Start with research. Deliver value. Leverage email and social. Then—and only then—call with context. You’re no longer the teacher like when you were knocking on doors. 3. This is how modern sales works. And this is how trust is built at scale. Welcome to the future, my friends. 🙌🏾 #NervousSystemsStrategist #SalesLeadership #ModernSelling #ColdCalling #SalesDevelopment #InsightSelling #SalesStrategy #SalesEnablement

People are suffering—yet many still deny that hours with ChatGPT reshape how we focus, create and critique. A new MIT study, “Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay-Writing,” offers clear neurological evidence that the denial is misplaced. Read the study (lengthy but far more enjoyable than a conventional manuscript, with a dedicated TL;DR and a summarizing table for the LLM): https://lnkd.in/g6PBVwVe 🧠 What the researchers did - Fifty-four students wrote SAT-style essays across four sessions while high-density EEG tracked information flow among 32 brain regions. - Three tools were compared: no aid (“Brain-only”), Google search, and GPT-4o. - In Session 4 the groups were flipped: students who had written unaided now rewrote with GPT (Brain→LLM), while habitual GPT users had to write solo (LLM→Brain). ⚡ Key findings - Creativity offloaded, networks dimmed. Pure GPT use produced the weakest fronto-parietal and temporal connectivity of all conditions, signalling lighter executive control and shallower semantic processing. - Order matters. When students first wrestled with ideas on their own and then revised with GPT, brain-wide connectivity surged and exceeded every earlier GPT session. Conversely, writers who began with GPT and later worked without it showed the lowest coordination and leaned on GPT-favoured vocabulary, making their essays linguistically bland despite high grades. - Memory and ownership collapse. In their very first GPT session, none of the AI-assisted writers could quote a sentence they had just penned, whereas almost every solo writer could; the deficit persisted even after practice. - Cognitive debt accumulates. Repeated GPT use narrowed topic exploration and diversity; when AI crutches were removed, writers struggled to recover the breadth and depth of earlier human-only work. 🌱 So what? The study frames this tradeoff as cognitive debt: convenience today taxes our ability to learn, remember, and think later. Critically, the order of tool use matters. Starting with one’s ideas and then layering AI support can keep neural circuits firing on all cylinders, while starting with AI may stunt the networks that make creativity and critical reasoning uniquely human. 🤔 Where does that leave creativity? If AI drafts faster than we can think, our value shifts from typing first passes to deciding which ideas matter, why they matter, and when to switch the autopilot off. Hybrid routines—alternate tools-free phases with AI phases—may give us the best of both worlds: speed without surrendering cognitive agency. Further reading: Lively discussion (debate) between neuroethicist Nita Farahany and CEO of The Atlantic, Nicholas Thompson, “The Most Interesting Thing in AI” podcast. The big (and maybe the final) question for us is: What is humanity when AI takes over all the creative processes? Podcast link: https://lnkd.in/emeQkcK6

I almost fired our best SDR last year. It wasn’t personal. He was a good guy, worked hard, and always showed up on time. But month after month, his numbers weren’t improving. Emails went unanswered. Calls never connected. Demos? Non-existent. We were both frustrated. I started to wonder if he was the problem. Maybe sales wasn’t his thing? Then one afternoon, we grabbed coffee. Instead of talking numbers, we talked openly. I asked him straight-up: “Why isn’t it working?” He took a deep breath and replied: “I’m following our playbook. I send hundreds of emails, but honestly, I’m just guessing. I don’t really know who’s ready to talk, so I try everyone.” It hit me like a ton of bricks. We’d built a system based on volume and hope, not precision. It wasn’t him. it was us. We’d given him the wrong tools, the wrong strategy. So instead of letting him go, we completely changed how we did outbound. We stopped guessing. We started paying attention to signals: Who’s visiting our LinkedIn profiles? (Tracked via Teamfluence™) Who’s engaging silently with our posts? (Tracked via Clay) Who’s spending serious time on our website? (Tracked via RB2B) Suddenly, our SDR wasn’t sending cold messages. He was following signals that said, “Hey, I’m interested. Talk to me.” Within a month, his reply rate doubled. In two months, he became our top performer. Today, he leads our outbound team. It wasn’t about effort. It was about timing and having a system that showed him exactly when to reach out and who to reach out to. Outbound isn’t about sending more messages. It’s about knowing exactly when and how to engage. If your SDRs are struggling, ask yourself: Are they failing you or are you failing them? It might change your perspective. It certainly changed ours. #Outbound #SalesLeadership #SDRlife #RevOps #LinkedInSales #SalesLessons #GTMStrategy #B2BSaaS #SmartSelling #GTMEngineering #AIOutbound #Teamfluence #Clay

"Feedback is a gift. It's an opportunity to learn and grow" At Google, we believe in the power of feedback to drive improvement. Sometimes feedback can be tough to hear. But taking the time to unpack it, understand the perspective, and reflect on it is crucial. Why feedback matters: - It reveals blind spots we cannot see ourselves - It accelerates learning by shortcutting trial and error - It demonstrates that others are invested in your success - It creates alignment between perception and reality How to receive feedback effectively: 1. Approach with curiosity, not defensiveness When receiving feedback, your first reaction might be to justify or explain. Instead, listen deeply and ask clarifying questions: "Can you give me a specific example?" or "What would success look like to you?" 2. Separate intention from impact Remember that well-intentioned actions can still have unintended consequences. Focus on understanding the impact rather than defending your intentions. 3. Look for patterns across multiple sources Individual feedback may reflect personal preferences, but patterns across multiple sources often reveal genuine opportunities for growth. 4. Prioritize actionable insights Not all feedback requires action. Evaluate which points will have the greatest impact on your effectiveness and focus your energy there. 5. Follow up and close the loop Demonstrate your commitment by acknowledging the feedback, sharing your action plan, and following up on your progress. Creating a feedback-rich environment: - Model vulnerability by asking for feedback yourself - Recognize and celebrate when people implement feedback successfully - Make it routine through structured check-ins rather than waiting for formal reviews At Google, we've learned that organizations with robust feedback cultures innovate faster, adapt more quickly to market changes, and build more inclusive workplaces. Let's commit to seeing feedback not as criticism but as a valuable investment in our collective future. The discomfort is temporary, but the growth is lasting. #motivation #productivity #mindset

In any workplace, an inverse relationship exists between training and development and the disengagement of your people. It's subtle, however it's there and painfully evident. Investing in our people’s personal development can mitigate disengagement and represents a prime opportunity to enhance individual performance. Here's why: “The space between our practiced values (in reality what we do, think, and feel) and our aspirational values (what we want to do, think, and feel) is the value gap or disengagement divide.” This quote from Brené Brown informs us that many in our workforce don’t value their jobs because they are not being fulfilled, either personally or professionally. They are disengaged. John Maxwell Company Facilitator and Coach, Perry Holley, backed this up on a recent edition of the Maxwell Executive Leadership podcast, "The bottom line from our research indicates that, on any given team, about 70% of the people aren't helping to row the boat". That equates to 7 of every 10 team members being disengaged, either not knowing how to do their job correctly, or not contributing. How do we explain this? Simply stated by Holley, “these are people who aren't being actively developed.” He further shares "as a leader, you can influence the engagement level of people on your team when you invest in developing them each as individuals." When people are involved with development activities, they act on personal experience and aspirations as part of a plan that focuses on their individual development. They are closing their value gap. When we are acting on any activity that improves the organization, we are involved in execution. Execution is what gets us to the results we need. Developing your people helps with everything from improving daily performance and increasing retention, providing them with new skills needed for personal and career growth. Training and development provides people with a worldview much larger than they could acquire on their own. It excites them about their work and the possibilities it holds for their future. Here's another good reason to commit to your people. No one individual believes that they're bad at their job. Think about that statement and you can understand the two main reasons why; 1) no one has ever given them constructive feedback on their performance, or 2) no one has bothered to spend time with them to help them personally develop. Even the smallest investment of time spent learning something new or working with someone experienced has value to a team member. If the boat carrying your team isn't moving as fast and efficiently as it could be check to see who's not rowing, and then ask them how their personal development plan is going. The answer they share might surprise you. #ceos #leadership #peopledevelopment #execution Development can start here, check out https://lnkd.in/gXpc_pyu for more tips and leadership wisdom.